Clinical Prediction Rule for Patient Outcome after In-Hospital CPR: A New Model, Using Characteristics Present at Hospital Admission, to Identify Patients Unlikely to Benefit from CPR after In-Hospital Cardiac Arrest.

BACKGROUND: Physicians and patients frequently overestimate likelihood of survival after in-hospital cardiopulmonary resuscitation. Discussions and decisions around resuscitation after in-hospital cardiopulmonary arrest often take place without adequate or accurate information. METHODS: We conducted a retrospective chart review of 470 instances of resuscitation after in-hospital cardiopulmonary arrest. Individuals were randomly assigned to a derivation cohort and a validation cohort. Logistic Regression and Linear Discriminant Analysis were used to perform multivariate analysis of the data. The resultant best performing rule was converted to a weighted integer tool, and thresholds of survival and nonsurvival were determined with an attempt to optimize sensitivity and specificity for survival. RESULTS: A 10-feature rule, using thresholds for survival and nonsurvival, was created; the sensitivity of the rule on the validation cohort was 42.7% and specificity was 82.4%. In the Dartmouth Score (DS), the features of age (greater than 70 years of age), history of cancer, previous cardiovascular accident, and presence of coma, hypotension, abnormal PaO2, and abnormal bicarbonate were identified as the best predictors of nonsurvival. Angina, dementia, and chronic respiratory insufficiency were selected as protective features. CONCLUSIONS: Utilizing information easily obtainable on admission, our clinical prediction tool, the DS, provides physicians individualized information about their patients' probability of survival after in-hospital cardiopulmonary arrest. The DS may become a useful addition to medical expertise and clinical judgment in evaluating and communicating an individual's probability of survival after in-hospital cardiopulmonary arrest after it is validated by other cohorts.

Comparison of blood volume pulse and skin conductance responses to mental and affective stimuli at different anatomical sites.

Measurements of blood volume pulse (BVP) and skin conductance are commonly used as indications of psychological arousal in affective computing and human-machine interfaces. To date, palmar surfaces remain the primary site for these measurements. Placement of sensors on palmar surfaces, however, is undesirable when recordings are fraught with motion and pressure artifacts. These artifacts are frequent when the human participant has involuntary movements as in hyperkinetic cerebral palsy. This motivates the use of alternative measurement sites. The present study examined the correlation between measurements of blood volume pulse and skin conductance obtained from three different sites on the body (fingers, toes and ear for BVP; fingers, toes and arch of the foot for skin conductance) in response to cognitive and affective stimuli. The results of this pilot study indicated significant inter-site correlation among signal features derived from different sites, with the exception of BVP amplitude, the number of electrodermal reactions and the slope of the electrodermal activity response. We attribute these differences in part to inter-site discrepancies in local skin conditions, such as skin temperature. Despite these differences, significant changes from baseline were present in the responses to the cognitive and affective stimuli at non-palmar sites, suggesting that these sites may provide viable signal measurements for use in affective computing and human-machine interface applications.